mlsanityData to 14 Oct 2026

HalluCana: Fixing LLM Hallucination with A Canary Lookahead

arXiv 2412.07965 ↗First posted 10 Dec 2024cs.CLcited by 1

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Abstract (arXiv)

In this paper, we present HalluCana, a canary lookahead to detect and correct factuality hallucinations of Large Language Models (LLMs) in long-form generation. HalluCana detects and intervenes as soon as traces of hallucination emerge, during and even before generation. To support timely detection, we exploit the internal factuality representation in the LLM hidden space, where we investigate various proxies to the LLMs' factuality self-assessment, and discuss its relation to the models' context familiarity from their pre-training. On biography generation, our method improves generation quality by up to 2.5x, while consuming over 6 times less compute.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 27 of its 40 references that are in the map. First posted on arXiv 10 Dec 2024.

Builds on

27 of 40 references.

References · 27

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  2. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 13,028
  3. 2022Self-Consistency Improves Chain of Thought Reasoning in Language Modelscited by 5,708
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  6. 2022Language Models (Mostly) Know What They Knowcited by 1,856
  7. 2023Inference-Time Intervention: Eliciting Truthful Answers from a Language Modelcited by 1,302
  8. 2023FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generationcited by 1,282
  9. 2021DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharingcited by 1,254
  10. 2022Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Taskscited by 868
  11. 2023The RefinedWeb Dataset for Falcon LLM: Outperforming Curated Corpora with Web Data, and Web Data Onlycited by 763
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15 more
  1. 2023The Internal State of an LLM Knows When It's Lyingcited by 659
  2. 2023The Falcon Series of Open Language Modelscited by 535
  3. 2022Large Language Models Struggle to Learn Long-Tail Knowledgecited by 458
  4. 2023Check Your Facts and Try Again: Improving Large Language Models with External Knowledge and Automated Feedbackcited by 353
  5. 2024Semantic Entropy Probes: Robust and Cheap Hallucination Detection in LLMscited by 259
  6. 2024LLMs Know More Than They Show: On the Intrinsic Representation of LLM Hallucinationscited by 244
  7. 2023A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generationcited by 206
  8. 2022Factuality Enhanced Language Models for Open-Ended Text Generationcited by 202
  9. 2023Sources of Hallucination by Large Language Models on Inference Taskscited by 169
  10. 2023Head-to-Tail: How Knowledgeable are Large Language Models (LLMs)? A.K.A. Will LLMs Replace Knowledge Graphs?cited by 168
  11. 2021NeuroLogic A*esque Decoding: Constrained Text Generation with Lookahead Heuristicscited by 154
  12. 2023Still No Lie Detector for Language Models: Probing Empirical and Conceptual Roadblockscited by 78
  13. 2022ReFinED: An Efficient Zero-shot-capable Approach to End-to-End Entity Linkingcited by 74
  14. 2023Faithfulness-Aware Decoding Strategies for Abstractive Summarizationcited by 31
  15. 2023Correction with Backtracking Reduces Hallucination in Summarizationcited by 4

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Citing papers per year: 2025: 1.

1 paper.

  1. 2025Loki's Dance of Illusions: A Comprehensive Survey of Hallucination in Large Language Modelscited by 7